Style translation for human motion
Year: 2005
Type: article
Abstract: Style translation is the process of transforming an input motion into a new style while preserving its original content. This problem is motivated by the needs of interactive applications, which require rapid processing of captured performances. Our solution learns to translate by analyzing differences between performances of the same content in input and output styles. It relies on a novel correspondence algorithm to align motions, and a linear time-invariant model to represent stylistic differences. Once the model is estimated with system identification, our system is capable of translating streaming input with simple linear operations at each frame.
Source: ACM Transactions on Graphics
Authors: Eugene Hsu, Kari Pulli, Jovan Popović
Institution: Massachusetts Institute of Technology
Language: English
Topic: Human Motion and Animation
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2112539290